Dynamics of PCBs in the Food Web of Lake Winnipeg
Sarah B. Gewurtz, Nilima Gandhi, Gary A. Stern, William G. Franzin, Bruno Rosenberg,
and Miriam L. Diamond
Appendix
TABLE A-1. Physical-chemical properties of PCBs considered in model simulations.
Chemical
PCB 28
PCB 52
PCB 101
PCB 105
PCB 118
PCB 138
PCB 153
PCB 180
1
2
Molecular
weight
(g/mol)
257.5
292.0
326.4
326.4
326.4
360.9
360.9
395.3
Log Kow
(25 ºC)1,2
∆Uow3
Melting
point4 (ºC)
AH5,6
BH5,6
5.67
5.84
6.38
6.65
6.07
6.83
6.92
7.36
-22000
-23000
-24000
-24000
-24000
-25000
-25000
-26000
57.0
87.0
77.4
118.5
109.0
80.0
103.5
110.0
12.0
13.2
13.6
13.6
13.6
13.9
14.1
14.7
3100
3352
3531
3601
3601
3757
3662
3910
data from Hawker and Connell (1988).
Kow values adjusted for temperature as follows (Beyer et al. 2002, Li et al. 2003):
logK ow (T) = logK ow (25° C) +
n∆ U ow ⋅ (1 T− 1 298.15)
ln(10) ⋅ R
where TK is temperature (K), ∆Uow is the internal energy of phase transfer between
octanol and water (J/mol), and R is the universal gas constant (J/mol·K).
3
data from Li et al. (2003).
4
data from Mackay et al. (1992).
5
Henry’s Law constants adjusted for temperature as follows (Paasivirta et al. 1999):
B
logH = A H − H
T
where AH and BH are constants that have been derived by Paasivirta et al. (1999).
6
data from Paasivirta et al. (1999).
1
Gewurtz et al.
Appendix
TABLE A-2. Dietary compositions (% volume) in the south basin of Lake Winnipeg.
Predator↓
Zoo
Clam
Chironomid
Mayfly
Cisco
Whitefish
Shiner
Sauger
Walleye
Food prey→
Detritus Phyto
100
50
60
40
60
40
20
80
Zoo
Clam
Chironomid
Mayfly
Shiner
10
33
10
33
30
33
10
10
10
10
80
80
50
30
20
2
Gewurtz et al.
Appendix
TABLE A-3. Dietary compositions (% volume) in the north basin of Lake Winnipeg.
Predator↓
Zoo
Clam
Chironomid
Mayfly
Cisco
Whitefish
Shiner
Smelt
Sauger
Walleye
Food prey→
Detritus Phyto
60
60
100
50
40
40
20
80
30
Zoo
Clam
Chironomid
Mayfly
33
10
33
10
33
10
10
Shiner
Smelt
50
30
20
50
30
100
100
3
Gewurtz et al.
Appendix
TABLE A-4. Definition of symbols used in the food web model.
Parameter
fW, fD, fB
DuW, DD, DeW, DF,
DG, DM
ZB, ZW, ZD, ZG
GW
GD
GF
kuW
keW
kg
MT
Eox
Ew
ED
Cox
WB
VB
KDG
FL, FN, FW
FLG, FNG, FWG
FLD, FND, FWD
εL, εN, εW
Vpl
Units
Pa
mol/Pa/hr
Definition
Fugacities in water, diet, and organism, respectively
Mass transport or transformation parameters describing
contaminant uptake from water, uptake from diet, and
elimination through water, through feces, through growth, and
through metabolic transformation
mol/m3/Pa Fugacity capacities in the organism, water, diet, and gut
contents, respectively
m3/hr
Rate of water ventilation across the respiratory surface
m3/hr
Food ingestion rate
m3/hr
Fecal egestion rate
1/hr
Rate constant for chemical uptake from water via the gills for
animals or from water to phytoplankton cell for phytoplankton
1/hr
Rate constant for chemical elimination from the organism to
the water via the gills
1/hr
Growth rate constant
mg O2/hr Total energy metabolism
unitless Maximum efficiency of oxygen transfer across the gills
unitless Efficiency of contaminant transfer across the respiratory
surface and the organism
unitless Efficiency of contaminant transfer between the gut contents
and the organism
mg O2/L Concentration of dissolved oxygen in water
kg wet
Organism weight
weight
m3
Organism volume (approximated as WB/1000)
unitless Organism diet to GIT partition coefficient
unitless Lipid fraction, non-lipid organic matter fraction, and water
fraction, respectively, in the organism
unitless Lipid fraction, non-lipid organic matter fraction, and water
fraction, respectively, in the GIT contents
unitless Lipid fraction, non-lipid organic matter fraction, and water
fraction, respectively, in the organism diet
unitless Absorption efficiencies of lipid, nonlipid organic matter, and
water from the ingested diet
unitless Volume fraction of plankton and other suspended solids in the
water column
4
TABLE A-5. Equations used in the food web model.
Fish
Ref.
Zooplankton and Detrital benthos
Ref.
Ref.
Phytoplankton
Ref.
-
Filter
feeding
benthos
Same as fish
DuW
G W E W ZW
1
Same as fish
-
k uW VBZW
1
GW
M T E ox Cox
2
Same as fish
-
Same as fish
-
-
-
3
9
MT
0.67log(W B * 1000) + 0.017T − 0.77
exp (−6.66 + 0.80ln(10 WB ⋅ (1 − FW )) + 0.12T )
8
Same as fish
-
-
-
Cox
(14.45 − 0.413T + 0.00556T 2 ) 1000
2
Same as fish
-
Same as fish
-
-
-
kuW
-
-
-
-
-
-
EW
(1.85 + (155 /K ow (25° C)) −1
4
Same as fish
-
Same as fish
-
-
-
DD
G DE D ZD
1
Same as fish
-
Same as fish
-
-
-
GD
9.2 × 10 −7 WB0.85exp(0.06T)
5
Same as fish
-
G W Vpl
9
-
-
ED
(3.0 × 10 −7 ⋅ K ow (25°C) + 2.0) −1
4
Same as fish
-
Same as fish
-
-
-
DF
DD * ( 1 − β )
K DG
6
Same as fish
-
Same as fish
-
-
-
((6.0 × 10
−5
+ (5.5/K ow )) −1 )/24
4
β
nε L FLD +nε N FND +nε W FWD
4
Same as fish
-
Same as fish
-
-
-
KDG
FLD + 0.035FND + FWD K ow
FLG + 0.035FNG + FWG K ow
4
Same as fish
-
Same as fish
-
-
-
FLG
(1 −nε L ) ⋅ FLD
(1 −nε L ) ⋅ FLD + (1 −nε N ) ⋅ FND + (1 −nε W ) ⋅ FWD
(1 − nε N ) ⋅ FND
(1 −nε L ) ⋅ FLD + (1 − ε N ) ⋅ FND + (1 −nε W ) ⋅ FWD
(1 −nε W ) ⋅ FWD
(1 −nε L ) ⋅ FLD + (1 −nε N ) ⋅ FND + (1 −nε W ) ⋅ FWD
4
Same as fish
-
Same as fish
-
-
-
4
Same as fish
-
Same as fish
-
-
-
4
Same as fish
-
Same as fish
-
-
-
DG
VB Z Bk G
1
Same as fish
-
Same as fish
-
-
kg
0.00586(1.113)T − 20 * (WB * 1000)−0.2
7
Same as fish
-
Same as fish
-
FNG
FWG
5
(0.10(W
B
× 10
−12 −0.15
)
)/ 24
10
Gewurtz et al.
Appendix
1
equation from Campfens and Mackay (1997).
equation from Norstrom et al. (1976).
3
equation from Gewurtz et al. (2006).
4
equation from Arnot and Gobas (2004).
5
equation from Weininger (1978).
6
equation from Gandhi et al. (2006)
7
equation from Thomann (Thomann 1981, Thomann et al. 1992). This equation is used to calculate growth only for those fish where
measured growth rates are not available (i.e. equation used for cisco, whitefish, and emerald shiner). Measured growth rates are used
for sauger and walleye in the south basin and walleye in the north basin.
8
equation from Devol (1979).
9
equation from Morrison et al. (1996). We assume a Vpl value of 0.007 according to Patalas and Salki (1992) who found that the
average volume of suspended solids in the water column between June and August in both basins is approximately 0.007 ± 0.001
(mean ± SE) m3/m3.
10
equation from Tang (1995). The kG values were standardized to 20 ºC and are temperature corrected using a Q10 value of 1.58
2
6
Gewurtz et al.
Appendix
TABLE A-6. Species-specific input values used to characterize the food web of the south basin of Lake
Winnipeg.
Species
Phytoplankton
Zooplankton
Clams
Chironomids
Mayfly larvae
Cisco
Whitefish
Emerald Shiner
Sauger
Walleye
n
0
10
0
0
2
10
9
0
11
10
WB1
1.5E-14
2.4E-08
6.0E-03
4.0E-05
1.0E-04
0.13
1.32
0.0028
0.273
0.324
Eox2
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
FL3
0.005
0.018
0.002
0.03
0.06
0.014
0.056
0.024
0.0063
0.0056
1
FN4
0.195
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
εL4
0.72
0.75
0.75
0.75
0.75
0.75
0.92
0.92
0.92
εN4
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
εW5
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
kg6
1.9 × 10-5
4.6 × 10-5
data measured except for phytoplankton weight which was obtained from Malone (1980),
zooplankton weight which was obtained from Hansen et al. (1997), chironomid and mayfly
larvae weights which was obtained from Pennak (1978), and shiner weight which was estimated
from Scott and Crossman (1973).
2
estimated.
3
data measured except for phytoplankton lipid content which was obtained from Arnot and
Gobas (2004), zooplankton lipid content which was estimated as the lipid content of net
plankton, chironomid lipid content which was approximated as two times the lipid content of
mayflies (Gardner et al. 1985, Landrum and Poore 1988), and shiner lipid content which was
estimated from Russell et al. (1995).
4
data from Arnot and Gobas (2004).
5
data from Olsen and Ringo (1998).
6
calculated from the slope of length versus age using geometric mean regression (Gewurtz
2005). Data are presented only for species where age data were collected.
7
Gewurtz et al.
Appendix
TABLE A-7. Species-specific input values used to characterize the food web of the north basin of Lake
Winnipeg.
Species
Phytoplankton
Zooplankton
Clams
Chironomids
Mayfly larvae
Cisco
Whitefish
Smelt
Emerald Shiner
Sauger
Walleye
n
0
12
0
0
2
10
10
8
0
8
9
WB1
1.5E-14
2.4E-08
6.0E-03
4.0E-05
1.0E-04
0.580
0.826
0.0087
0.0028
0.798
0.855
Eox2
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
FL3
0.005
0.0095
0.0017
0.032
0.016
0.048
0.020
0.0055
0.024
0.016
0.016
1
FN4
0.195
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
εL4
0.72
0.75
0.75
0.75
0.75
0.75
0.75
0.92
0.92
0.92
εN4
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
εW4
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
kg5
4.0E-06
data measured except for phytoplankton weight which was obtained from Malone (1980),
zooplankton weight which was obtained from Hansen et al. (1997), chironomid and mayfly
larvae weights which was obtained from Pennak (1978), and shiner weight which was estimated
from Scott and Crossman (1973).
2
estimated.
3
data measured except for phytoplankton lipid content which was obtained from Arnot and
Gobas (2004), zooplankton lipid content which was estimated as the lipid content of net
plankton, chironomid lipid content which was approximated as two times the lipid content of
mayflies (Gardner et al. 1985, Landrum and Poore 1988), and shiner lipid content which was
estimated from Russell et al. (1995).
4
data from Arnot and Gobas (2004).
5
data from Olsen and Ringo (1998).
6
calculated from the slope of length versus age using geometric mean regression (Gewurtz
2005). Data are presented only for species where age data were collected.
8
Gewurtz et al.
Appendix
PCB 28
ln concentration (ng/g lipid)
PCB 101
PCB 52
lnPCB28 = 0.21(±0.06)δ15N – 1.9(±0.98)
p<0.001, r2=0.51
3
lnPCB52 = 0.17(±0.06)δ15N – 0.39(±0.94)
p<0.001, r2=0.42
4
5
2
3
4
1
2
3
0
1
2
-1
0
5
10
15
1
5
20
10
PCB 105
4
15
20
lnPCB105 = 0.19(±0.06)δ N – 0.84(±0.80)
p<0.001, r2=0.54
lnPCB118 = 0.19(±0.06)δ N + 0.24(±0.82)
p<0.001, r2=0.51
3
1
2
0
15
20
P CB 138
2
5
10
15
20
5
10
P CB 180
4
3
3
2
2
15
20
To tal P CB
5
lnPCB153 = 0.19(±0.06)δ15N + 0.84(±0.86)
p<0.001, r2=0.52
4
20
3
P CB 153
5
15
4
1
10
10
lnPCB138 = 0.19(±0.06)δ15N + 1.0(±0.84)
p<0.001, r2=0.51
5
15
4
2
5
5
PCB 118
5
15
3
lnPCB101 = 0.16(±0.04)δ15N – 0.76(±0.74)
p<0.001, r2=0.50
8
lnPCB180 = 0.22(±0.06)δ15N - 0.14(±0.98)
p<0.001, r2=0.50
lnTotalPCB = 0.17(±0.06)δ15N + 3.7(±0.88)
p<0.001, r2=0.44
7
6
1
5
10
15
20
5
4
3
1
5
10
15
20
5
10
15
20
δ15N (‰)
FIG. A-1. The natural logarithm of concentration (ng/g lipid) versus δ15N in the south basin
food web of Lake Winnipeg. Error bars represent 95% confidence intervals.
9
Gewurtz et al.
Appendix
lnPCB28 = 0.14(±0.10)δ15N – 1.0(±1.32)
p<0.05, r2=0.12
3.0
3.0
lnPCB52 = 0.16(±0.08)δ15N – 1.0(±1.06)
p<0.001, r2=0.24
2.5
2.0
2.5
1.5
1.5
1.0
1.0
1.0
0.5
0.5
0.0
-1.0
0.0
-0.5
4
8
12
4
16
8
P CB 105
1.5
0.5
0.0
-0.5
2.5
2.5
1.5
16
0.5
0.0
4
8
2.5
2.0
1.5
1.0
0.5
0.0
8
12
12
16
4
8
PCB 180
lnPCB153 = 0.19(±0.06)δ15N + 0.01(±0.80)
3.0 p<0.001, r2=0.40
16
16
1.0
PCB 153
3.5
12
lnPCB138 = 0.17(±0.06)δ15N + 0.21(±0.78)
p<0.001, r2=0.37
3.0
2.0
0.0
12
3.5
1.0
-1.5
4
8
PCB 138
1.5
0.5
8
4
16
lnPCB118 = 0.15(±0.06)δ15N – 0.28(±0.80)
p<0.001, r2=0.30
2.0
-1.0
4
12
PCB 118
lnPCB105 = 0.14(±0.06)δ15N – 1.2(±0.76)
p<0.001, r2=0.29
1.0
lnPCB101 = 0.14(±0.06)δ15N – 0.09(±0.99)
p<0.001, r2=0.37
2.0
2.0
0.0
ln concentration (ng/g lipid)
P CB 101
P CB 52
PCB 28
4.0
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
12
16
Total PCB
lnPCB180 = 0.20(±0.08)δ15N – 1.1(±0.88)
p<0.001, r2=0.39
6.5
lnTotalPCB = 0.11(±0.08)δ15N + 3.5(±0.88)
p<0.01, r2=0.17
6.0
5.5
5.0
4.5
4.0
3.5
3.0
4
8
12
16
4
8
12
16
δ15N (‰)
FIG. A-2. The natural logarithm of concentration (ng/g lipid) versus δ 15N in the north basin
food web of Lake Winnipeg. Error bars represent 95% confidence intervals.
10
Gewurtz et al.
Appendix
South Basin
North Basin
20
17
Walleye
18
δ15N (‰)
16
Sauger
15
Sauger
Walleye
Emerald
shiner
Cisco
13
Cisco
Emerald
shiner
14
Mayfly
11
Smelt
Whitefish
Whitefish
12
9
10
Plankton
Mayfly
7
8
Plankton
5
6
-50
-40
-30
-20
-10
-50
0
-30
-10
10
δ13C (‰)
FIG. A-3. Mean (±95% confidence intervals) stable nitrogen (δ 15N) and carbon (δ 13C) isotope
values in the south and north basin food webs of Lake Winnipeg.
11
Gewurtz et al.
Appendix
REFERENCES
Arnot, J. A., and Gobas, F. A. P. C. 2004. A food web bioaccumulation model for organic
chemicals in aquatic ecosystems. Environ. Toxicol. Chem. 23:2343-2355.
Beyer, A., Wania, F., Gouin, T., Mackay, D., and Matthies, M. 2002. Selecting internally
consistent physicochemical properties of organic compounds. Environ. Toxicol. Chem.
21:941-953.
Campfens, J., and Mackay, D. 1997. Fugacity-based model of PCB bioaccumulation in complex
aquatic food webs. Environ. Sci. Technol. 31:577-583.
Devol, A. H. 1979. Zooplankton respiration and its relation to plankton dynamics in two lakes of
contrasting trophic state. Limnol. Oceanogr. 24:893-905.
Gandhi, N., Bhavsar, S. P., Gewurtz, S. B., Diamond, M. L., Evenset, A., Christensen, G. N., and
Gregor, D. 2006. Development of a multi-chemical food chain model: Application to
PBDE in Lake Ellasjoen, Bear Island. Environ. Sci. Technol. In press.
Gardner, W. S., Nalepa, T. F., Frez, W. A., Cichocki, E. A., and Landrum, P. F. 1985. Seasonal
patterns in lipid-content of Lake Michigan macroinvertebrates. Can. J. Fish. Aquat. Sci.
42:1827-1832.
Gewurtz, S. B. 2005. An evaluation of factors controlling the dynamics of PCBs in aquatic food
webs: A modeling approach, PhD Dissertation, University of Toronto, Toronto, ON,
Canada.
Gewurtz, S. B., Laposa, R., Gandhi, N., Christensen, G. N., Evenset, A., Gregor, D., and
Diamond, M. L. 2006. A comparison of contaminant dynamics in arctic and temperate
fish: A modeling approach. Chemosphere 63:1328-1341.
Hansen, P. J., Bjornsen, P. K., and Hansen, B. W. 1997. Zooplankton grazing and growth:
Scaling within the 2-2000 mu m body size range. Limnol. Oceanogr. 42:687-704.
Hawker, D. W., and Connell, D. W. 1988. Octanol-water partition coefficients of polychlorinated
biphenyl congeners. Environ. Sci. Technol. 22:382-387.
Landrum, P. F., and Poore, R. 1988. Toxicokinetics of selected xenobiotics in hexagenia
limbata. J. Great Lakes Res. 14:427-437.
Li, N. Q., Wania, F., Lei, Y. D., and Daly, G. L. 2003. A comprehensive and critical
compilation, evaluation, and selection of physical-chemical property data for selected
polychlorinated biphenyls. J. Phys. Chem. Ref. Data 32:1545-1590.
Mackay, D., Shiu, W. Y., and Ma, K. C. 1992. Illustrated Handbook of Physical-Chemical
Properties and Environmental Fate for Organic Chemicals: Monoaromatic Hydrocarbons,
Chlorobenzenes, and PCBs. Chelsea, MI, USA: Lewis.
Malone, T. C. 1980. Algal size. In The physiological ecology of phytoplankton, eds. I. Morris,
pp. 433-463. Oxford: Blackwell Scientific Publications.
Morrison, H. A., Gobas, F. A. P. C., Lazar, R., and Haffner, G. D. 1996. Development and
verification of a bioaccumulation model for organic contaminants in benthic
invertebrates. Environ. Sci. Technol. 30:3377-3384.
Norstrom, R. J., McKinnon, A. E., and deFreitas, A. S. W. 1976. A bioenergetics based model
for pollutant accumulation by fish. Simulation of PCB and methyl mercury residue levels
in Ottawa River yellow perch (Perca flavescens). J. Fish. Res. Board Can. 33:248-267.
Olsen, R. E., and Ringo, E. 1998. The influence of temperature on the apparent nutrient and fatty
acid digestibility of arctic charr, Salvelinus alpinus L. Aquaculture Res. 29:695-701.
12
Gewurtz et al.
Appendix
Paasivirta, J., Sinkkonen, S., Mikkelson, P., Rantio, T., and Wania, F. 1999. Estimation of vapor
pressures, solubilities and Henry's law contants of selected persistent organic pollutants
as functions of temperature. Chemosphere 39:811-832.
Patalas, K., and Salki, A. 1992. Crustacean plankton in Lake Winnipeg: variation in space and
time as a function of lake morphology, geology and climate. Can. J. Fish. Aquat. Sci.
49:1035-1059.
Pennak, R. W. 1978. Fresh-water Invertebrates in the United States. New York, NY, USA: John
Wiley & Sons.
Russell, R. W., Lazar, R., and Haffner, G. D. 1995. Biomagnification of organochlorines in Lake
Erie white bass. Environ. Toxicol. Chem. 14:719-724.
Scott, W. B., and Crossman, E. J. 1973. Freshwater Fishes of Canada. Ottawa, ON, Canada:
Fisheries Research Board of Canada.
Tang, E. P. Y. 1995. The allometry of algal growth rates. J. Plankton Res. 17:1325-1335.
Thomann, R. V. 1981. Equilibrium model of fate of microcontaminants in diverse aquatic food
chains. Can. J. Fish. Aquat. Sci. 38:280-296.
Thomann, R. V., Connolly, J. P., and Parkerton, T. F. 1992. Modelling accumulation of organic
chemicals in aquatic food-webs. In Chemical dynamics in aquatic ecosystems, eds. F. A.
P. C. Gobas and J. A. McCorquodale, pp. 153-186. Chelsea, MI, USA: Lewis Publishers.
Weininger, D. 1978. Accumulation of PCBs by lake trout in Lake Michigan, Ph.D. Dissertation,
University of Wisconsin, Madison, WI, USA.
13